Biometric systems are gaining in popularity as a convenient, secure way to authenticate a person's identity to a computer or other system, device, environment, information or information system or database, or other protected or limited access capability. This allows systems to grant or deny access to a particular user. Access can be to a service, to information, or to a physical entity such as room. Fingerprints, used by the Federal Bureau of Investigation (FBI) and other law enforcement and forensic agencies for decades, are a very reliable means of verifying identity. Most conventional automatic fingerprint systems in use today consist of an electronic fingerprint sensor, a host computer such as a small general purpose or personal computer (PC) or computer processing unit, and fingerprint comparison and matching software that can analyze and compare a fingerprint image to one (or one of a large set stored in a fingerprint database) stored previously, for instance a fingerprint acquired and stored during enrollment for some sort of employment, military service, drivers license registration, law enforcement arrest and incarceration, or other service, or for any other reason.
Fingerprints all consist of physical ridges and valleys on the surface of the finger, as shown in FIG. 1B. In this figure ridges are in black and valleys are in white. Interesting minutiae points used for matching are identified either by rectangles overlaid on the image to indicate a ridge ending or by a circle to indicate a bifurcation. The two-dimensional pattern of ridges and valleys has proven to be unique among very large populations of human beings, especially the ridge endings and bifurcations called or referred to a fingerprint “minutiae.”
Electronic fingerprint sensors, until about the mid-1990's, were all designed to actively sense the entire surface of a fingerprint at the same time and were frequently referred to as contact or placement sensors. Whether based on optical or electrical sensing methods, all such sensors were designed to be at least as large as a typical person's fingertip (typically about 15 cm×15 cm) or at least the portion of significance having the minutiae. The user simply placed his or her finger tip on the sensor device until the image was captured. These devices are now known as placement sensors and they capture large images, typically ranging from 250–500 rows and 200–500 columns depending on the sensor's capabilities and size. These sensors were satisfactory for some applications where the space occupied by the sensor (and possibly by supporting electronics associated with the sensor) could be tolerated. In many instances size had not been an issue because the relatively large surface of for example even a portable device such as a notebook computer adjacent the keyboard may have been available for such placement. Other applications may have provided for a separate box or enclosure for the placement sensor, again reducing the importance of physical size.
However, as companies worked to reduce the cost of fingerprint sensing devices, they soon realized the only way to do that would be to reduce the actual size of the device, at least in part because the cost of the fingerprint sensor increases dramatically as the size increases, particularly for silicon based sensors where cost increases as a function of silicon area. Miniaturization was and still is a very desirable trait for a fingerprint sensor, because aside from the cost reduction, the smaller a sensor the easier it is to embed such sensors in common devices such as laptop computers, PDAs, mobile phones, or other information appliances or communication devices.
The most promising of the miniaturization approaches involves creating a sensor that is fully sized in one direction (typically in width) but abbreviated in the other (typically height). It is appreciated that width and height are somewhat arbitrary descriptions of the two orthogonal sensor dimensions. This results in a sensor that only is capable of sensing a small rectangular portion of the finger at any one time. Unlike placement sensors, a user must sweep his or her finger along the device in order to capture a full image of the finger. As the user sweeps, the rectangular slices, or frames, take snapshots of the finger as it moves by. The width dimension is captured each time and the other dimension is built up from combinations of the abbreviated height dimensions. To create an image for use by standard fingerprint processing systems, the individual frames must then be aligned, and redundant information thrown away, in order to generate or “reconstruct” the desired image corresponding to the original object (fingertip portion) so that the seams between frames are not apparent in the generated or reconstructed image. If this could be done well, then the resulting reconstructed image would look indistinguishable from images captured with a placement sensor of the same type that collects or acquires an image of the original object all at the same time.
One example of a fingerprint swipe sensor is described in U.S. Pat. No. 6,289,114 entitled FINGERPRINT-READING SYSTEM, incorporated by reference herein. This patent describes a system in which the surface area of this sensor is far smaller than the surface area of the fingerprint to be read. The reading is done when the sensor and the finger are in contact and in a relative motion of sliding of the sensor and the finger with respect to each other. The system reconstitutes a complete image of the fingerprint from the partial images given by the sensor during this motion. The manner in which the system reconstitutes a complete image of the fingerprint from the partial images given by the sensor is not described.